Zhu, Songyan und Zeng, Qiaolin und Zhu, Hao und Xu, Jian und Gu, Jianbin und Wang, Yongqian und Chen, Liangfu (2021) An optimization approach for hourly ozone simulation: a case study in Chongqing, China. IEEE Geoscience and Remote Sensing Letters, 18 (11), Seiten 1871-1875. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LGRS.2020.3010416. ISSN 1545-598X.
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Offizielle URL: https://ieeexplore.ieee.org/document/9153854
Kurzfassung
Continuous spatial knowledge is required to control the regional ozone pollution. Measurements from ground-level sites are beneficial to this goal, but their number is limited due to the huge expenses of site establishment, operation, and maintenance. Remote sensing seems a promising data source, but its application is challenged by bad weather conditions. Always covered by thick clouds, Chongqing, a populated industrial city in west China, is facing serious ozone pollution, but relevant studies here are relatively insufficient. Another alternative is estimating ozone by models. Well-performed models degrade in Chongqing partially due to the very complex terrain. Modeled hourly ozone does not agree with ground-level measurements. Therefore, an optimization approach is proposed to improve model estimates for such regions. This approach integrates the ground-level information (e.g., measured ozone and meteorology) through the employment of ResNet (Residual Network). ResNet overcomes the notorious vanishing gradient issue in classic neural networks, and the ability of learning complex systems is largely boosted. Ozone distribution is like a gray image that varies every second, which is not the case usually learned by ResNet. A color-image alike data structure is raised to address this ``nonstill image'' problem; according to the Taylor Expansion, polynomials can describe a complex system, and the errors are acceptable. To facilitate the usage in business operations, this approach is designed to be robust, inexpensive, and easy to use. The scheme of control site selection is discussed in detail. In cross-validations, this approach performs well, averaged R² is higher than 0.9 and the error is less than 5 μ g/m³.
elib-URL des Eintrags: | https://elib.dlr.de/137986/ | ||||||||||||||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||||||||||||||
Titel: | An optimization approach for hourly ozone simulation: a case study in Chongqing, China | ||||||||||||||||||||||||||||||||
Autoren: |
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Datum: | November 2021 | ||||||||||||||||||||||||||||||||
Erschienen in: | IEEE Geoscience and Remote Sensing Letters | ||||||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||||||||||
Band: | 18 | ||||||||||||||||||||||||||||||||
DOI: | 10.1109/LGRS.2020.3010416 | ||||||||||||||||||||||||||||||||
Seitenbereich: | Seiten 1871-1875 | ||||||||||||||||||||||||||||||||
Verlag: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||||||||||||||||||
ISSN: | 1545-598X | ||||||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||||||
Stichwörter: | China National Environmental Monitoring Centre (CNEMC), image recognition, nested air quality prediction modeling system (NAQ-PMS), ozone pollution, ResNet, thick clouds. | ||||||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Atmosphären- und Klimaforschung | ||||||||||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > Atmosphärenprozessoren | ||||||||||||||||||||||||||||||||
Hinterlegt von: | Xu, Dr.-Ing. Jian | ||||||||||||||||||||||||||||||||
Hinterlegt am: | 25 Nov 2020 15:50 | ||||||||||||||||||||||||||||||||
Letzte Änderung: | 01 Jan 2023 03:00 |
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